{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b46c848e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d11d6e2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[0.6987, 0.7744, 0.5740, 0.5246, 0.8816, 0.7458, 0.3271, 0.8091, 0.1065,\n",
       "         0.5792, 0.2914, 0.3695, 0.6498, 0.8346, 0.3288, 0.5982, 0.9344, 0.2660,\n",
       "         0.7944, 0.6792, 0.3329, 0.0936, 0.7269, 0.4131, 0.8313, 0.3192, 0.8437,\n",
       "         0.3187, 0.0054, 0.1089, 0.2276, 0.9165, 0.2009, 0.6523, 0.4387, 0.3410,\n",
       "         0.1771, 0.2438, 0.8465, 0.6802, 0.1743, 0.7312, 0.7315, 0.2181, 0.7013,\n",
       "         0.7754, 0.3678, 0.1901, 0.1734, 0.3132, 0.0391, 0.0206, 0.9281, 0.0797,\n",
       "         0.2530, 0.1841, 0.2549, 0.8732, 0.3898, 0.9259, 0.5612, 0.6723, 0.6910,\n",
       "         0.8939, 0.4806, 0.7854, 0.8497, 0.0637, 0.5937, 0.0495, 0.2158, 0.4473,\n",
       "         0.6136, 0.2601, 0.8151, 0.8773, 0.1644, 0.9765, 0.0291, 0.3065, 0.2580,\n",
       "         0.7637, 0.2592, 0.4901, 0.3354, 0.3050, 0.2510, 0.0951, 0.2355, 0.4311,\n",
       "         0.1830, 0.1714, 0.9326, 0.2013, 0.4918, 0.7479, 0.9574, 0.7188, 0.0904,\n",
       "         0.8492]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = torch.rand(1,100)\n",
    "x"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pytorch",
   "language": "python",
   "name": "pytorch"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
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